1. Field of the Invention
The present invention relates generally to nuclear reactors, and more particularly to determining a fresh fuel bundle design for a core of a nuclear reactor.
2. Description of the Related Art
A boiling water reactor (BWR) or pressurized water reactor (PWR) typically operates from one to two years before requiring fuel replacement. This period is referred to as a fuel cycle or energy cycle. Upon completion of a cycle, approximately ¼ to ½ (typically about ⅓) of the least reactive fuel in the reactor core is discharged to a spent fuel pool. The number of fuel assemblies (e.g., fuel bundles) discharged typically are replaced by an equal number of fresh fuel bundles (“fresh bundles”).
The fresh bundles may vary in bundle average enrichment (the average % of enriched uranium (U235) and poisons (such as gadolinium) across the fresh fuel bundle, determined by the total weight of U235 and gadolinium in the bundle divided by the weight of the bundle). The fresh bundles may also vary in their local peaking characteristics, exposure peaking, R-factor characteristics, and overall exposure dependent reactivity, each of which may represent local bundle limits.
The exposure dependent local peaking factor of a fresh bundle may be determined from the maximum local peaking value in any one fuel rod of the fresh bundle in question. The higher the local peaking factor, the higher the Maximum Fraction of Limiting Power Density (MFLPD) and Maximum Average Planar Linear Heat Generation Rate (MAPLHGR), which are power-related limits on nuclear fuel for the core, or global core limits. The R-factor for each rod of a bundle is defined with respect to the correlation employed for bundle Critical Power Ratio (CPR), a power-related fuel limit for the core, and is calculated for each rod as a weighted average of the axially integrated rod powers in the vicinity of the given rod. In other environments, alternate correlations for CPR may exist that reference R-factor by another term that is similarly based on a weighted average of rod powers within the bundle. The R-Factor for a fresh bundle may be determined from the maximum R-Factor in any rod of the fresh bundle in question. Likewise, the higher the R-factor, the higher the Maximum Fraction of Limiting Critical Power Ratio (MFLCPR), which is also a power-related fuel limit for the core. MFLCPR measures the allowable margin between operating conditions and a limit to ‘dryout’, explained in further detail below.
When coolant in a core can no longer remove heat at a sufficient rate, the fuel and clad temperature will start to increase rapidly. This boiling transition condition may be known as film dryout, burnout, departure from nucleate boiling, etc., depending on the actual conditions leading to the temperature excursion. For BWR fuel, the boiling transition phenomenon may be referred to as dryout. An R-factor value may be a value correlating thermal hydraulic variables (such as flow rate, inlet subcooling, system pressure, hydraulic diameter) to the axially integrated fuel rod power distribution within the bundle. Exposure peaking is related to the integral of the local peaking of each individual fuel rod and is constrained by the maximum licensed exposure capability of the fuel.
Because local peaking and R-factor values in any fuel bundle are directly proportional to core thermal limits such as MAPLHGR limits (KW/ft limits) and MFLCPR limits, it is beneficial to effectively determine local peaking and R-factor values at each exposure. Determining accurate local peaking and R-factor values at each exposure during a core or fuel bundle design phase may aid efforts to design fresh fuel bundles that meet core performance criteria for a specified reactor plant, so as not to violate any of the core thermal limits, while still meeting other criteria such as bundle average enrichment, hot-to-cold swing (reactivity excursion at beginning of cycle (BOC) from hot, uncontrolled conditions to cold, controlled conditions), and overall exposure dependent reactivity. Exposure peaking should also be considered in determining a fresh fuel bundle design or configuration for a core, as a high exposure peaking factor limits the maximum bundle exposure and therefore the maximum reload enrichment that can be loaded in the reactor.
Fresh bundle design is currently an iterative process. The designer uses information from the cycle energy requirements, operating limits, and thermal limits of a given core being modeled to create a bundle design with a target average enrichment, number of gadolinium rods, and average gadolinium concentration. The fresh bundle design is then modeled using various computer codes (lattice physics, cross-section fitting, R-factor calculation, etc.) known as bundle design codes, as part of a bundle simulation. The fresh bundle design is then inserted into a core simulator, which is a software program that simulates reactor operation with a ‘virtual core’ configured with the fresh bundle design. The designer analyzes the results of the core simulation to modify the fresh bundle design. The modified fresh bundle design is then analyzed in the bundle design codes again (bundle simulation) and reactor operations for a virtual core loaded in accordance with the modified bundle design is simulated in the core simulator (core simulation) for verification. The designer may iteratively repeat these steps until the design requirements are satisfied, such as all target thermal limits met, target power satisfied, etc.
This iterative approach to fresh bundle design is a time-consuming, inefficient process. The input files and execution files for all the various computer codes have to be created and run in the correct order. An interactive-GUI program (IBNDL) may be used to automate most of these tasks, but still requires significant user intervention at various stages in the process. After the bundle calculations, the fresh bundle design is added to the core simulator input manually or by using another interactive-GUI program. There is thus no automation and consolidation of the various computer codes onto one platform. In addition, this iterative approach can lead to bundle designs consisting of complicated rod designs and configurations that can increase manufacturing time.